Method and apparatus for estimating channel characteristics using pilot and non-pilot data

ABSTRACT

Techniques for incorporating non-pilot symbols along with pilot symbols to improve the estimate of the characteristics (e.g., amplitude and phase) of a communication link. A pilot filter weighs samples corresponding to pilot and non-pilot symbol by different sets of coefficients, which have values determined by and/or corresponding to the confidence in the detected sample. Samples corresponding to pilot symbols are typically associated with higher degree of confidence and are weighted more (e.g., with weights of 1.0). Samples corresponding to non-pilot symbols are typically associated with lower confidence and are weighted with values that may be variable and dependent on the degree of confidence in the samples (e.g., with weights ranging from 0.0 up to 1.0). The weights are updated based on a particular estimator such as a MAP (Maximum a Posteriori) estimator, a MLE (Maximum Likelihood Estimator), or some other estimator.

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional PatentApplication No. 60/264,621, filed Jan. 26, 2001, and entitled “PilotFilter Incorporating Non-Pilot Symbols.”

BACKGROUND

[0002] 1. Field

[0003] The present invention relates generally to data communication,and more specifically to techniques for estimating the characteristics(e.g., amplitude and phase) of a communication link using pilot andnon-pilot data.

[0004] 2. Background

[0005] Wireless communication systems are widely deployed to providevarious types of communication such as voice, packet data, and so on.These systems may be based on code division multiple access (CDMA), timedivision multiple access (TDMA), or some other modulation techniques.CDMA systems may provide certain advantages over other types of system,including increased system capacity.

[0006] For many wireless communication systems, a pilot is transmittedalong with signaling and traffic data (e.g., voice and/or packet data)from a transmitter unit to a receiver unit. The pilot is typically aknown data pattern that is processed and modulated in a known manner.Signaling and traffic data are also processed and modulated viarespective schemes, combined with the processed pilot, and transmittedto the receiver unit. The transmitted pilot allows the receiver unit toestimate the communication link used to transmit signaling and trafficdata.

[0007] At the receiver unit, a rake receiver is often used to recoverthe transmitted pilot, signaling, and traffic data. The transmittedsignal may be received via multiple signal paths (or multipaths), andeach received multipath may be processed by a respective fingerprocessor of the rake receiver. Each finger processor processes thepilot in a complementary manner to derive a pilot reference havingamplitude and phase determined by the characteristics of that multipath.The pilot reference is typically used to coherently demodulate thesignaling and traffic data, which are transmitted along with the pilotand are similarly distorted by the propagation path. The pilotreferences for the received multipaths are also used to combine thedemodulated multipaths to derive an improved estimate of the transmittedsignaling and traffic data.

[0008] The quality of the pilot reference directly impacts theperformance of the demodulation process, which in turn determines theperformance of the communication system. A higher quality pilotreference may be obtained by transmitting the pilot from the transmitterunit at higher transmit power level. However, since the amount ofavailable transmit power is limited, transmitting the pilot at a higherpower level consumes more resources and decreases the amount of poweravailable for signaling and traffic data.

[0009] There is therefore a need in the art for techniques capable ofproviding a higher quality pilot reference based on the transmittedpilot, signaling, and (possibly) traffic data.

SUMMARY

[0010] Aspects of the invention provide techniques for incorporatingnon-pilot symbols along with pilot symbols to improve the estimate ofthe characteristics (e.g., amplitude and phase) of a communication link.A pilot filter described herein weighs samples corresponding to pilotand non-pilot symbol by different sets of coefficients, which havevalues determined by and/or corresponding to the confidence in thedetected sample. Samples corresponding to pilot symbols are typicallyassociated with higher degree of confidence and are weighted more (e.g.,with weights of 1.0). Samples corresponding to non-pilot symbols aretypically associated with lower confidence and are weighted with valuesthat may be variable and dependent on the degree of confidence in thesamples (e.g., with weights ranging from 0.0 up to 1.0). The weights maybe updated based on a particular estimator such as a MAP (Maximum aPosteriori) estimator, a MLE (Maximum Likelihood Estimator), or someother estimator.

[0011] An embodiment of the invention provides a method for generatingpilot estimates indicative of the characteristics (e.g., amplitude andphase) of a communication link. In accordance with the method, samplescorresponding to pilot symbols and non-pilot symbols are initiallyreceived. Samples corresponding to pilot symbols are weighted inaccordance with a first set of one or more coefficients to provide firstweighted samples, and samples corresponding to non-pilot symbols areweighted in accordance with a second set of one or more coefficients toprovide second weighted samples. The pilot estimates are then generatedbased on the first and second weighted samples.

[0012] The coefficients for pilot symbols can have equal magnitude(e.g., 1.0), and the coefficients for non-pilot symbols can havemagnitude equal to or less than that of the pilot symbol coefficients.The coefficients for non-pilot symbol can be updated in accordance witha particular function and further based on (1) the received samplescorresponding to non-pilot symbols, (2) the pilot estimates, and (3) aterm indicative of the quality of the received samples used to updatethe coefficients. In this manner, the coefficients for non-pilot symbolscan be updated to larger values if the quality of the samples is high,and to lower values if the quality of the samples is low.

[0013] Various approximations may be made to simplify the computationsfor updating the coefficients and weighting the received samples. Forexample, the coefficients may be quantized to 5 bits or less, thefunction used to update the coefficients may be approximated with apiece-wise linear function, one or more terms in the function may beapproximated with constants, and so on.

[0014] The techniques described herein may be used for any communicationsystem in which pilot and non-pilot symbols are transmitted (e.g., in atime-division multiplexed manner) and may be advantageously used invarious CDMA systems (e.g., a cdma2000 system, a W-CDMA system, andothers).

[0015] The invention further provides other methods, apparatus, andelements that implement various aspects, embodiments, and features ofthe invention, as described in further detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The features, nature, and advantages of the present inventionwill become more apparent from the detailed description set forth belowwhen taken in conjunction with the drawings in which like referencecharacters identify correspondingly throughout and wherein:

[0017]FIG. 1 is a diagram of a wireless communication system thatsupports a number of users and capable of implementing various aspectsof the invention;

[0018]FIG. 2 is a simplified block diagram of the processing for anuplink transmission from a remote terminal to a base station;

[0019]FIG. 3 is a diagram of a frame format and a slot format for anuplink dedicated physical channel as defined by the W-CDMA standard;

[0020]FIGS. 4A through 4C are diagrams of three embodiments of a pilotfilter capable of providing an improved estimate of the channelcharacteristics based on pilot and non-pilot symbols;

[0021]FIG. 5 is a block diagram of an embodiment of a rake receivercapable of implementing various aspects of the invention; and

[0022]FIG. 6 shows plots of a tanh function and a piece-wiseapproximation of the tanh function, which may be used to derive thecoefficients for the pilot filter.

DETAILED DESCRIPTION

[0023]FIG. 1 is a diagram of a wireless communication system 100 thatsupports a number of users and capable of implementing various aspectsof the invention. System 100 provides communication for a number ofcells, with each cell being serviced by a corresponding base station104. The base stations are also commonly referred to as base transceiversystems (BTS). Various remote terminals 106 are dispersed throughout thesystem. Each remote terminal 106 may communicate with one or more basestations 104 on the downlink and uplink at any particular moment,depending on whether or not the remote terminal is active and whether ornot it is in soft handoff. The downlink (i.e., forward link) refers totransmission from base station 104 to remote terminal 106, and theuplink (i.e., reverse link) refers to transmission from remote terminal106 to base station 104. As shown in FIG. 1, base station 104 acommunicates with remote terminals 106 a, 106 b, 106 c, and 106 d, andbase station 104 b communicates with remote terminals 106 d, 106 e, and106 f. Remote terminal 106 d is in soft handoff and concurrentlycommunicates with base stations 104 a and 104 b.

[0024] In system 100, a base station controller (BSC) 102 couples tobase stations 104 and may further couple to a public switched telephonenetwork (PSTN) via a mobile switching center (MSC), which is not shownin FIG. 1 for simplicity. The BSC may also couple into a packet networkvia a packet data serving node (PDSN), which is also not shown inFIG. 1. BSC 102 provides coordination and control for the base stationscoupled to it. BSC 102 further controls the routing of telephone callsamong remote terminals 106, and between remote terminals 106 and userscoupled to the PSTN (e.g., conventional telephones) and to the packetnetwork, via base stations 104.

[0025] The system 100 can be designed to support one or more CDMAstandards such as the IS-95, IS-98, cdma2000, W-CDMA, some other CDMAstandard, or a combination thereof. These CDMA standards are known inthe art and incorporated herein by reference.

[0026] Various aspects and embodiments of the invention can be appliedto both the uplink and downlink in a wireless communication system. Forclarity, various aspects and embodiments of the invention are nowspecifically described for the uplink in a W-CDMA system.

[0027]FIG. 2 is a simplified block diagram of the processing for anuplink transmission from remote terminal 106 to base station 104. Atremote terminal 106, voice and/or packet data (i.e., traffic data) andcontrol data (i.e., signaling) are provided to a transmit (TX) dataprocessor 212, which formats and encodes the data with one or morecoding schemes to generate coded data. Each coding scheme may includeany combination of cyclic redundancy check (CRC), convolutional, Turbo,block, and other coding, or no coding at all. Voice, packet, and controldata are typically coded using different schemes, and different types ofcontrol data may also be coded differently.

[0028] The coded data is then provided to a modulator (MOD) 214 andfurther processed (e.g., covered, spread with short PN sequences, andscrambled with a long PN sequence assigned to the user terminal) togenerate modulated data. Pilot data is also typically processed inaccordance with another scheme to provide modulated pilot. The modulateddata and pilot are combined and provided to a transmitter unit (TMTR)216 and conditioned (e.g., converted to one or more analog signals,amplified, filtered, and quadrature modulated) to generate an uplinksignal that is transmitted via an antenna 220 to base station 104.

[0029] At base station 104, the uplink signal is received by an antenna250 and provided to a receiver unit (RCVR) 254. Receiver unit 254conditions (e.g., filters, amplifies, downconverts, and digitizes) thereceived signal and provides samples. A demodulator (DEMOD) 256 receivesand processes (e.g., despreads, decovers, and pilot demodulates) thesamples to provide recovered symbols. Demodulator 256 may implement arake receiver that processes multiple instances of the received signaland generates combined symbols. A receive (RX) data processor 258 thendecodes the symbols to recover the traffic data and signaling that weretransmitted on the uplink. The processing by demodulator 256 and RX dataprocessor 258 are complementary to that performed at remote terminal106. Demodulator 256 is described in further detail below.

[0030] For some wireless systems, a pilot is transmitted along withsignaling and traffic data from the base station to the remoteterminals, and vice versa. The transmitted pilot is used by thereceiving unit to coherently demodulate signaling and traffic datatransmitted along with the pilot.

[0031]FIG. 3 is a diagram of a frame format and a slot format for anuplink dedicated physical channel as defined by the W-CDMA standard.Generally, different frame formats are defined by the W-CDMA standardfor the uplink and downlink, and a different frame format is furtherdefined for each type of physical channel such as the dedicated physicalchannel (DPCH). The traffic data to be transmitted on each physicalchannel is partitioned into radio frames, with each radio frameincluding 15 slots labeled as slot 0 through slot 14. Each slot isfurther partitioned into one or more fields that are used to carrytraffic, control, and pilot data.

[0032] As shown in FIG. 3, the uplink dedicated physical channelincludes a dedicated physical data channel (DPDCH) and a dedicatedphysical control channel (DPCCH), which are respectively transmitted onthe inphase (I) and quadrature (Q) components of a modulated uplinksignal. The DPDCH carries user-dedicated packet data, and the DPCCHcarries control data (including pilot data). Each slot of the DPCCHincludes a transmit power control (TPC) field, a feedback information(FBI) field, an optional transport format combination indicator (TFCI)field, and a pilot field. The TPC field is used to send power controlinformation to direct the base station to adjusts its transmit power onthe downlink channels either up or down to achieve the desiredperformance while minimizing interference. The TFCI field is used tosend instantaneous parameters (e.g., the bit rate, channelization code,and so on) of the transport channels multiplexed on the uplink DPDCH.The FBI field is used to support techniques requiring feedback betweenthe user terminal and base station, such as various transmit diversitymodes. The pilot field is used to send pilot data for the dedicatedphysical channel.

[0033] Because of limited system resources, a tradeoff is made betweenusing the channel to send pilot data and traffic and control data. Manynewer generation CDMA systems transmit the pilot in a time divisionmultiplexed (TDM) manner along with other control data on a physicalchannel. In fact, the pilot symbols may comprise only a portion (e.g.,20% to 50%) of the non-traffic symbols transmitted on the physicalchannel. The pilot symbols are associated with a known data pattern andcan be used to estimate the characteristics of the communication link.The other control symbols are typically not known a priori by the basestation.

[0034] In one simple design, only the pilot symbols are processed by apilot filter to recover a pilot reference, which is then used tocoherently demodulate the traffic data. In this design, other controlsymbols are simply ignored, and the pilot filter is maintained (i.e.,not updated) during non-pilot symbol periods. However, when a largepercentage (e.g., 50%) of the non-traffic symbols are not pilot symbols,the performance of the pilot filter (i.e., the channel estimates) maydegrade noticeably, since there may be a gap (of up to five non-pilotsymbols) between successive pilot symbols.

[0035] In accordance with an aspect of the invention, non-pilot symbolsare also used to improve the performance of the pilot filter. Anestimator is employed to use as much available information as possibleto estimate the desired channel qualities, which for data demodulationare the gain and phase of the channel used for the data transmission.

[0036] The received signal may be processed and digitized to provide(complex-value) samples. The samples corresponding to each receivedmultipath may be processed by an assigned finger processor of a rakereceiver, as described in further detail below. If there are N_(T)ontime samples (i.e., properly aligned in time), of which N_(P) samplescorrespond to pilot symbols and the remaining samples correspond tonon-pilot symbols, then the samples may be expressed as: $\begin{matrix}{y_{i} = \left\{ {\begin{matrix}{{A \cdot ^{j\quad \phi}} + n_{i}} \\{{A \cdot ^{j\quad \phi} \cdot b_{i}} + n_{i}}\end{matrix}\begin{matrix}{{i = 1},\ldots \quad,N_{P}} \\{{i = {N_{P} + 1}},\ldots \quad,N_{T}}\end{matrix}} \right.} & {{Eq}\quad (1)}\end{matrix}$

[0037] Where n_(i) is the channel noise having the properties ofn_(i)˜CN(0,σ²) and independent and identically distributed (iid), b_(i)is the value of the non-pilot symbol (i.e., b_(i) ∈ {−1, 1}) and iid,and A and φ are the channel amplitude and phase, respectively. The phaseφ is typically used to remove the phase ambiguity from the data in afinger processor of a rake receiver (described below), and the amplitudeA is used to properly combine the results across multiple assignedfinger processors. The quantities A and φ may be estimated using a MAP(Maximum a Posteriori) estimator, an MLE (Maximum Likelihood Estimator),or some other estimator. The MAP estimator may provide a more optimalestimate of A and φ in comparison to those from other estimators.

[0038] The MAP estimator provides the solution to the following:$\begin{matrix}{{\max\limits_{A,\phi}p_{A,{\phi|\underset{\_}{y}}}},} & {{Eq}\quad (2)}\end{matrix}$

[0039] Where y is a vector of N_(T) samples (i.e., y=[y₁,y₂, . . . ,y_(N) _(T) ]^(T)) and p_(A,φ|y) is the joint probability distributionfunction (pdf) of A and φ given y. Equation (2) may be manipulated asfollows: $\begin{matrix}\begin{matrix}{{\max\limits_{A,\phi}\quad p_{A,{\phi \underset{\_}{y}}}} \equiv \quad {\max\limits_{A,\phi}{p_{{\underset{\_}{y}A},\phi}p_{A}{p_{\phi}/p_{\underset{\_}{y}}}}}} \\{\equiv \quad {\max\limits_{A,\phi}{p_{{\underset{\_}{y}A},\phi}p_{A}}}} \\{{\equiv \quad {\max\limits_{A,\phi}{p_{A}{\prod\limits_{i = 1}^{N_{T}}\quad p_{y_{i}{{A,\phi}}}}}}},}\end{matrix} & {{Eq}\quad (3)}\end{matrix}$

[0040] where $\begin{matrix}{{\prod\limits_{i = 1}^{N_{T}}p_{{y_{i}A},\phi}} = {^{\frac{N_{T}A^{2}}{2\sigma^{2}}}{\exp \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}{\sum\limits_{i = 1}^{N_{p}}y_{i}^{*}}} \right\}} \right)}{\prod\limits_{i = {N_{p} + 1}}^{N_{T}}{{\cosh \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}.}}}} & \text{Eq~~(4)}\end{matrix}$

[0041] The first equality in equation (3) is due to Bayes' Theorem andthe fact that A and φ are independent, the second equality is due to thefact that φ is uniform and that p _(y) is not a function of A or φ, andthe third equality is due to the fact that, given A and φ, the y_(i) areindependent. The natural logarithm of the argument in equation (3) maybe taken to yield the following: $\begin{matrix}{{\max\limits_{A,\phi}\quad {g(A)}} + {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}{\sum\limits_{i = 1}^{N_{p}}y_{i}^{*}}} \right\}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}{\ln \quad {\cosh \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}}}} & \text{Eq~~(5)}\end{matrix}$

[0042] where $\begin{matrix}{{g(A)} = \left\{ \begin{matrix}{{- \frac{A^{2}}{2}}\frac{N_{T}}{\sigma^{2}}} & {{MLE}\quad {\text{solution~~(}\text{A}\text{~~is~~"Uniform")}}} \\{{{- \frac{A^{2}}{2}}\left( {\frac{N_{T}}{\sigma^{2}} + \frac{1}{\sigma_{A}^{2}}} \right)} + {\ln \quad A}} & \begin{matrix}{\text{MAP}\text{~~solution~~(}\text{A}\text{~~is~~Rayleigh}} \\{\text{with~~second~~moment}\quad 2\sigma_{A}^{2}\text{)}}\end{matrix}\end{matrix} \right.} & \text{Eq~~(6)}\end{matrix}$

[0043] To find the optimal estimates of A and φ, the expression forequation (5) is solved. This can be achieved by first taking thederivative of equation (5) with respect to φ and setting the derivativeto zero, as follows: $\begin{matrix}{\frac{\partial}{\partial\phi} = {{{Im}\left\{ {^{j\phi}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}y_{i}^{*}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}{y_{i}^{*}\quad {\tanh \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack} \right\}} = 0.}} & \text{Eq~~(7)}\end{matrix}$

[0044] Next, the derivative of equation (5) is taken with respect to Aand set to zero, as follows $\begin{matrix}{{\frac{\partial}{\partial A} = {{{\sigma^{2}{g^{\prime}(A)}} + {{Re}\left\{ {^{j\phi}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}y_{i}^{*}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}{y_{i}^{*}\quad {\tanh \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack} \right\}}} = 0}},} & \text{Eq~~(8)}\end{matrix}$

[0045] where $\begin{matrix}{{g^{\prime}(A)} = \left\{ {\begin{matrix}{- \frac{{AN}_{T}}{\sigma^{2}}} & {\text{MLE}\text{~~solution}} \\{{- {A\left( {\frac{N_{T}}{\sigma^{2}} + \frac{1}{\sigma_{A}^{2}}} \right)}} + \frac{1}{A}} & {\text{MAP}\text{~~solution}}\end{matrix}.} \right.} & \text{Eq~~(9)}\end{matrix}$

[0046] To simplify the notation, the following is defined:$\begin{matrix}{{f\left( {A,\phi} \right)} = {{\frac{1}{N_{T}}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}y_{i}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}{y_{i}\quad {\tanh \left( {{Re}\left\{ {\frac{A\quad ^{j\phi}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack}.}} & \text{Eq~~(10)}\end{matrix}$

[0047] The first-order conditions on A and φ can then be expressed as:

Im{e ^(Jφ)ƒ*(A,φ)}=0,  Eq (11)

[0048] and $\begin{matrix}{{{g^{\prime}(A)} + {\frac{N_{T}}{\sigma^{2}}{Re}\left\{ {^{j\phi}{f^{*}\left( {A,\phi} \right)}} \right\}}} = 0.} & \text{Eq~~(12)}\end{matrix}$

[0049] The expression for f(A,φ) in equation (10) represents ageneralized pilot filter in which the samples y_(i) are weighteddifferently depending on whether they correspond to pilot symbols ornon-pilot symbols. For i=1, . . . N_(P), the samples correspond to pilotsymbols and are weighted by a value of 1.0. And for i=N_(P)+1, . . . ,N_(T), the samples correspond to non-pilot symbols and are weighted bytanh(Re{y_(l)*Ae^(Jφ)/σ²}).

[0050] Equation (10) represents a weighted decision feedback filter.When the signal-to-noise-plus-interface ratio (SNR) is high (i.e., σ² isa low value), there is greater likelihood of a non-pilot symbol beingreceived correctly, and the symbol is weighted more (i.e., with weightsapproaching ±1.0). Conversely, when the SNR is low (i.e., σ² is a highvalue), there is lower likelihood of the non-pilot symbol being receivedcorrectly, and the symbol is weighted less (i.e., with weightsapproaching ±0.0). Thus, the pilot filter retains the sign of the symboldecision but weighs the magnitude of the symbol by a value that isrelated to the confidence in the detected symbol value.

[0051] Equations (11) and (12) may be solved in an iterative manner.From equation (11), the phase φ may be expressed as follows:

φ=∠ƒ(A,φ),  Eq (13)

[0052] Where ∠ x denotes the phase of x. Equations (12) and (13) may becombined to provide the following: $\begin{matrix}{{g^{\prime}(A)} = {{- \frac{N_{T}}{\sigma^{2}}}{{{f\left( {A,\phi} \right)}}.}}} & \text{Eq~~(14)}\end{matrix}$

[0053] Equations (13) and (14) indicate that, given an initial estimateof A and φ, the successive estimates of A and φ may be derived asfollows: $\begin{matrix}{{g^{\prime}\left( {\hat{A}}_{k} \right)} = {{- \frac{N_{T}}{\sigma^{2}}}{{{f\left( {{\hat{A}}_{k - 1},{\hat{\phi}}_{k - 1}} \right)}}.}}} & {{Eq}\quad (15)}\end{matrix}$

[0054] The initial estimates of A and φ, which are respectively denotedas Â₀ and {circumflex over (φ)}₀, may be derived using only the N_(P)pilot symbols or as the current pilot filter output. For the MLEestimate, ${{g^{\prime}(A)} = {- \frac{{AN}_{T}}{\sigma^{2}}}},$

[0055] Which is given in equation (9), and

Â _(k)=|ƒ(Â _(k−1),{circumflex over (φ)}_(k−1))|.

[0056] And for the MAP estimate,${{g^{\prime}(A)} = {{- {A\left( {\frac{N_{T}}{\sigma^{2}} + \frac{1}{\sigma_{A}^{2}}} \right)}} + \frac{1}{A}}},$

[0057] which is also given in equation (9), and${\hat{A}}_{k} = {{{f\left( {{\hat{A}}_{k - 1},{\hat{\phi}}_{k - 1}} \right)}}{\frac{1 + \sqrt{1 + {\frac{4\sigma^{2}}{N_{T}}\left( {1 + \frac{\sigma^{2}}{N_{T}\sigma_{A}^{2}}} \right){{f\left( {{\hat{A}}_{k - 1},{\hat{\phi}}_{k - 1}} \right)}}^{- 2}}}}{2\left( {1 + \frac{\sigma^{2}}{N_{T}\sigma_{A}^{2}}} \right)}.}}$

[0058] As a result, equation (15) becomes:

{circumflex over (φ)}_(k)=∠ƒ(Â _(k−1),{circumflex over (φ)}_(k−1))

Â_(k)=λ|ƒ(Â _(k−1),{circumflex over (φ)}_(k−1))|,   Eq (16)

[0059] where $\begin{matrix}{\lambda = \left\{ \begin{matrix}1 & {{MLE}\quad {solution}} \\\frac{1 + \sqrt{1 + {\frac{4\sigma^{2}}{N_{T}}\left( {1 + \frac{\sigma^{2}}{N_{T}\sigma_{A}^{2}}} \right){{f\left( {{\hat{A}}_{k - 1},{\hat{\phi}}_{k - 1}} \right)}}^{- 2}}}}{2\left( {1 + \frac{\sigma^{2}}{N_{T}\sigma_{A}^{2}}} \right)} & {{MAP}\quad {solution}}\end{matrix} \right.} & {{Eq}\quad (17)}\end{matrix}$

[0060] From equation (17), it can be seen that the MAP solutionapproaches the MLE solution as σ²→0 and λ→1. In general, the MLEsolution is a special case of the MAP solution.

[0061] For clarity, an implementation for the MLE solution is providedbelow. The MAP solution is more complex, as shown in equation (17), butmay also be implemented. For the MLE solution, λ=1 and equation (16) maybe simplified as follows:

{circumflex over (φ)}_(k)=∠ƒ(Â _(k−1),{circumflex over (φ)}_(k−1))

Â_(k)=|ƒ(Â _(k−1),{circumflex over (φ)}_(k−1))|,

[0062] which implies that Â_(k)e^(Jφ) ^(_(k)) =ƒ(Â_(k−1),{circumflexover (φ)}_(k−1)).Equation (10) may then be rewritten as:${{f\left( {{\hat{A}}_{k},{\hat{\phi}}_{k}} \right)} = {\frac{1}{N_{T}}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}\quad y_{1}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}\quad {y_{i}\quad {\tanh \left( {{Re}\left\{ {\frac{{\hat{A}}_{k}^{J\quad {\hat{\phi}}_{k}}}{\sigma^{2}}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack}},$

[0063] which implies that: $\begin{matrix}{{{f\left( {{\hat{A}}_{k},{\hat{\phi}}_{k}} \right)} = \quad {\frac{1}{N_{T}}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}\quad y_{1}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}\quad {y_{i}\quad {\tanh \left( {\frac{1}{\sigma^{2}}{Re}\left\{ {{f\left( {{\hat{A}}_{k - 1},{\hat{\phi}}_{k - 1}} \right)}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack}},} & \quad\end{matrix}$

[0064] or more succinctly: $\begin{matrix}{f_{k} = {{\frac{1}{N_{T}}\left\lbrack {{\sum\limits_{i = 1}^{N_{p}}\quad y_{1}} + {\sum\limits_{i = {N_{p} + 1}}^{N_{T}}\quad {y_{i}\quad {\tanh \left( {\frac{1}{\sigma^{2}}{Re}\left\{ {f_{k - 1}y_{i}^{*}} \right\}} \right)}}}} \right\rbrack}.}} & {{Eq}\quad (18)}\end{matrix}$

[0065] As shown in equation (18), the pilot filter output ƒ_(k) may besolved in an iterative manner to obtain the magnitude and phaseestimates, Â_(k) and {circumflex over (φ)}_(k). Equation (18) may alsobe decomposed into two summations, with the left summation beingperformed over the pilot symbols and the right summation being performedover the non-pilot symbols.

[0066] A generalized filter structure may be designed to perform thesummations for equation (18). In particular, equation (18) may beimplemented with a finite impulse response (FIR) filter, an infiniteimpulse response (IIR) filter, or some other filter structure.

[0067] For a FIR pilot filter implementation, equation (18) may beexpressed as follows: $\begin{matrix}{{f_{k} = {\frac{1}{N_{T}}{\sum\limits_{i = 1}^{N_{T}}\quad {w_{i}^{(k)} \cdot y_{i}}}}},} & {{Eq}\quad (19)}\end{matrix}$

[0068] where $\begin{matrix}{w_{i}^{(k)} = \left\{ {\begin{matrix}1 & {{for}\quad y_{i}\quad {corresponding}\quad {to}\quad {pilot}\quad {symbols}} \\{\tanh \left( {\frac{1}{\sigma^{2}}{Re}\left\{ {f_{k - 1}y_{i}^{*}} \right\}} \right)} & {{for}\quad y_{i}\quad {corresponding}\quad {to}} \\\quad & {{non}\text{-}{pilot}\quad {symbols}}\end{matrix}.} \right.} & {{Eq}\quad (20)}\end{matrix}$

[0069] The index k in equations (19) may be modified from arepresentation of a pure iteration index to a hybriditeration/time-instant index. The pilot filter output at time instant k(for a causal FIR filter) can then be expressed as: $\begin{matrix}{{f_{k} = {\frac{1}{N_{T}}{\sum\limits_{i = 0}^{N_{T} - 1}\quad {w_{k - i}^{(k)} \cdot y_{k - i}}}}},} & {{Eq}\quad (21)}\end{matrix}$

[0070] Where w_(i) ^((k)) is given in equation (20). Equation (21) maybe implemented in various manners, some of which are described below.

[0071]FIG. 4A is a diagram of an embodiment of a FIR pilot filter 410 a,which may be used to provide an improved estimate of the channelcharacteristics based on samples corresponding to pilot and non-pilotsymbols. The samples y_(i) corresponding to pilot and non-pilot symbolsare provided to a number of (N_(T)−1) delay elements 412 a through 412 mcoupled in series. Each delay element 412 provides one sample of delay.At each time instant k, the sample y_(i) and the outputs of delayelements 412 a through 412 m are provided to multipliers 414 a through414 n, respectively. Each multiplier 414 also receives a correspondingcoefficient w_(i) ^((k)), multiplies (i.e., weighs) the received samplewith the coefficient, and provides a weighted sample to a summer 416 a.Summer 416 a sums the N_(T) weighted samples from multipliers 414 athrough 414 n and provides a weighted sum. A divider 418 a then receivesand scales the weighted sum by a factor of N_(T), which represents thelength of FIR filter 410 a, to provide the pilot filter output ƒ_(k) attime instant k.

[0072] Depending on the specific implementation, FIR pilot filter 410acan provide a pilot filter output value for each input sample or foreach group of N_(T) samples (e.g., once each slot). To provide one pilotfilter output value for each group of N_(T) samples, N_(T) samples areinitially loaded into delay elements 412 a through 412 m. Once all N_(T)samples have been loaded, the samples are weighted by the coefficients,summed together, and scaled by N_(T). The coefficients for multipliers412 a through 412 m are updated but do not change their position. Forexample, the coefficient for multiplier 414 a may correspond to anon-pilot symbol whereas the coefficient for multiplier 414 n maycorrespond to a pilot symbol.

[0073] To provide one pilot filter output value for each sample y_(i),the samples are again loaded into delay elements 412 a through 412 m.For each new input sample, the N_(T) samples are weighted by thecoefficients, summed together, and scaled by N_(T). The coefficients formultipliers 414 a through 414 m are updated (once for each group ofN_(T) samples) and further shifted to the right to track theircorresponding samples. For example, at time instant k, the sample y_(i)is weighted by coefficient w_(i) ^((k)) by multiplier 414 a. And at thenext time instant k+1, this same sample is provided from delay element412 a and weighted by the same coefficient by multiplier 414 b.

[0074] A coefficient adjustment unit 420 a receives the samples y_(i)and the pilot filter output ƒ_(k), and updates the coefficients for FIRfilter 410 a based on the received samples and pilot filter output andin accordance with equation (20). In particular, for the i-thcoefficient w_(i) ^((k)), the pilot filter output ƒ_(k−1) for theprevious time instance k−1 is multiplied with the complex conjugate ofthe sample, y_(i)*. The real part of the resultant product is thenscaled (i.e., divided) by σ². The tanh of the real part is thendetermined, and the resultant output comprises the i-th coefficientw_(i) ^((k)).

[0075]FIG. 4B is a diagram of another embodiment of a FIR pilot filter410 x, which may also be used to provide an improved estimate of thechannel characteristics based on samples corresponding to pilot andnon-pilot symbols. The samples y_(i) are provided, one sample at a time,to a multiplier 414 x. For each sample period, multiplexer 414 x alsoreceives a corresponding coefficient w_(i) ^((k)) from a coefficientadjustment unit 420 x. Multiplier 414 x weighs the received sample withthe coefficient and provides the weighted sample to a summer 416 x and astorage element 424 a. Summer 416 x also receives an output from asummer 426 x, sums the weighted sample from multiplier 414 x with theoutput from summer 426 x, and provides an accumulated total to a buffer422 x. Buffer 422 x maintains the accumulated total, which representsthe sum of N_(T) weighted samples. At each time instant k, a divider 418x receives and scales the accumulated total by a factor of N_(T), whichrepresents the number of samples accumulated, to provide the pilotfilter output ƒ_(k). For each input sample, summer 426 x receives theoldest weighted sample, y_(l−N) _(T) ₊₁·w_(t−N) _(T) ₊₁ ^((k)), fromstorage element 424 m and subtracts this weighted sample from the storedaccumulated total from buffer 422 x to provide an accumulated total forthe most recent (N_(T)−1) weighted samples. FIR pilot filter 410 x canprovide one pilot filter output value for each input sample.

[0076] A coefficient adjustment unit 420 x operates in similar manner asunit 420 a in FIG. 4A. Coefficient adjustment unit 420 x receives thesamples y_(i) and the pilot filter output ƒ_(k), and updates thecoefficients for FIR filter 410 x based on the received samples andpilot filter output and in accordance with equation (20). A controlsignal may be provided to ensure that the proper coefficient is updatedfor each received sample and that the proper coefficient is alsoprovided to multiplier 414 x for the received sample.

[0077] FIR pilot filter 410 x in FIG. 4B requires only one multiplier toimplement, and may be preferred over the filter implementation shown inFIG. 4A. As each sample y_(i) is received, it is weighted either with1.0 (if it corresponds to a pilot symbol) or withtanh(Re{ƒ_(k−1)y_(t)*/σ²}) (if it corresponds to a non-pilot symbol,where ƒ_(k−1) represents the previous pilot filter output). The weightedsample is then accumulated to generate the new pilot filter outputvalue.

[0078] For an IIR pilot filter implementation, equation (18) may beexpressed as follows:

ƒ_(k)=(1−α)ƒ_(k−1) +α·w _(i) ^((k)) ·y _(t),  Eq (22)

[0079] where w_(i) ^((k)) is given in equation (20), and the indices iand k correspond to the same time instance for the IIR implementation.The factor α determines the time constant for the IIR filter. A smallvalue for α(i.e., close to zero) weighs the sample y_(i) by a smallerfactor and results in a longer time constant for the IIR filter.Conversely, a large value for α(i.e., close to one) weighs the sampley_(i) by a larger factor and results in a shorter time constant for theIIR filter.

[0080]FIG. 4C is a diagram of an embodiment of an IIR pilot filter 410y, which may also be used to provide an improved estimate of the channelcharacteristics based on samples corresponding to pilot and non-pilotsymbols. The samples y_(i) are provided, one sample at a time, to amultiplier 414 y. For each input sample, multiplexer 414 y also receivesa corresponding scaled coefficient, α·w_(t) ^((k)), from a coefficientadjustment unit 420 y. Multiplier 414 y then weighs the received samplewith the coefficient and provides the weighted sample to a summer 416 y.Summer 416 y also receives the output from a multiplier 428 y, sumsoutputs from the two multipliers, and provides the pilot filter outputƒ_(k). A buffer 422 y receives and stores the pilot filter output ƒ_(k).Buffer 422 y further provides one sample of delay and provides thedelayed pilot filter output ƒ_(k−1) to multiplier 428 y. Multiplier 428y scales the delayed output ƒ_(k−1) with a scaling factor of (1−α). IIRpilot filter 410 y can provide a pilot filter output value for eachinput sample.

[0081] A coefficient adjustment unit 420 y operates in similar manner asunit 420 x in FIG. 4B. Coefficient adjustment unit 420 y receives thesamples and the pilot filter output, and updates the coefficients forIIR filter 410 y based on the received input samples and pilot filteroutput and in accordance with equation (20).

[0082]FIGS. 4A through 4C show three different designs of a pilot filterthat can provide improved channel estimates. Other designs for a pilotfilter that incorporates non-pilot symbols can also be contemplated andare within the scope of the invention.

[0083] As shown in equation (20), the filter coefficient w_(i) ^((k))includes a term for the variance of the noise σ². The value of σ² may beestimated in numerous ways, some of which are described below.

[0084] For a typical receiver implementation, an automatic gain control(AGC) circuit is used to set the amplitude of the input signal into theanalog-to-digital converter (ADC) such that the digitized samples,I_(ADC) and Q_(ADC), have a variance set at a particular value (e.g.,I_(o)). Specifically, the ADC input signal may be set such at E[I_(ADC)²+Q_(ADC) ²]=I_(o), where E[x] denotes the expected (or mean) value ofx, and I_(o) may be selected, for example, as 18 for 4-bit ADC samples.

[0085] The received energy I_(o) is composed of the received symbolenergy per chip E_(c) and the total noise energy N_(t). (i.e.,I_(o)=E_(c)+N_(t)). If the processing gain of the non-pilot symbol isN_(c) and the gain on a received symbol is g, then the noise variance σ²may be expressed as: $\begin{matrix}{{\sigma^{2} = \frac{N_{c} \cdot N_{t} \cdot g^{2}}{2}},} & {{Eq}\quad (23)}\end{matrix}$

[0086] where the division by 2 in equation (23) arises from theprojection of ƒ_(k−1)·y_(i)* to obtain the real part. So, if thereceiver employs an estimator for N_(t) (such as any of type ofestimator for N_(t) known in the art), then the value of σ² can bedetermined using equation (23). Alternatively, σ² may be approximatedwith a constant. That is, the received symbol energy E_(c) is typicallya small fraction of I_(o), in which case I_(o)≅N_(t) and equation (23)may be approximated as: $\begin{matrix}{\sigma^{2} \cong {\frac{N_{c} \cdot I_{o} \cdot g^{2}}{2}.}} & {{Eq}\quad (24)}\end{matrix}$

[0087] Other implementations different from that shown in equation (24)may also be used. In general, the noise variance may be determined as:

σ² h·I _(o),  Eq (25)

[0088] where h is a particular positive value.

[0089] To simplify the evaluation of the argument to the tanh functionin equation (20), 1/σ² may be implemented as: $\begin{matrix}{{\frac{1}{\sigma^{2}} \cong \frac{k}{2^{n}}},} & {{Eq}\quad (26)}\end{matrix}$

[0090] Where k and n are selected to achieve the desired level ofaccuracy. Using the approximation in equation (26), the evaluation ofthe argument to the tanh function, (1/σ²)·Re{ƒ_(k−1)·y_(i)*}, is thensimply a particular number of left and right shifts of the termRe{ƒ_(k−1)·y_(i)*}.

[0091] Various simplifications may be made to reduce the complexity ofthe pilot filter. In an embodiment, a limited number of filtercoefficients may be used. For example, a first coefficient (with a valueof 1.0) may be used for pilot symbols and a second coefficient (computedas shown in equation (20)) may be used for non-pilot symbols. The secondcoefficient may be updated in various manners such as (1) once for eachsample corresponding to a non-pilot symbol, (2) once for a group ofsamples corresponding to non-pilot symbols, or (3) once for each groupof (N_(T)−N_(P)) samples corresponding to non-pilot symbols.

[0092] If a limited number of coefficients are used, then othersimplifications may also be performed for the pilot filter. For example,a number of samples y_(i) may be accumulated prior to multiplicationwith the coefficients. This reduces the required number of multipliersand/or multiplications.

[0093]FIG. 6 is a plot of the tanh function used in equation (20) toderive the coefficients w_(i) ^((k)) for the pilot filter. The tanhfunction may be implemented in various manners, such as with a look-uptable. To reduce the complexity of the pilot filter, the tanh function(plot 610) may be approximated with a piece-wise linear function (plot612).

[0094] To further simplify the implementation of the pilot filter, thecoefficients for the pilot filter may be quantized to L bits, where Lcan be an integer selected to reduce the complexity of themultipliers/multiplications. For example, L may be selected as five, andthe coefficients may be quantized to nine possible values of ±{0, ¼, ½,¾, and 1 }. The quantization of the coefficients can greatly simplifythe multiplier/multiplication in the pilot filter. Simulations haveshown that the approximation of the tanh function with a piece-wiselinear function and the quantization of the coefficients to ninepossible values degrade the performance of the pilot filter by anegligible amount, if any.

[0095] The pilot filter described herein may be viewed as a filtercapable of weighing the samples y_(i) by different sets of coefficients,which have values determined by, and corresponding to, the confidence inthe detected value. The samples corresponding to pilot symbols aretypically associated with higher degree of confidence and are weightedmore (e.g., with weights of 1.0). The samples corresponding to non-pilotsymbols are typically associated with lower confidence and are weightedwith values that may be variable and dependent on the degree ofconfidence in the samples (e.g., with weights ranging from 0.0 up to1.0, or 0≦w_(i) ^((k))≦1.0).

[0096] The use of non-pilot symbols along with pilot symbols in thepilot filter can improve the estimate of the channel amplitude andphase. In fact, for some operating conditions applicable to a W-CDMAsystem, an improvement of up to 1.0 dB in the SNR for the pilot filteroutput may be achieved by incorporating non-pilot symbols in the pilotfilter. The higher pilot SNR can provide improved system performance,which may be quantified in terms of improved coded bit error rate (BER)or frame error rate (FER).

[0097]FIG. 5 is a block diagram of an embodiment of a rake receiver 256i a, which is a specific design for demodulator 256 in FIG. 2. Rakereceiver 256 a is also capable of implementing various aspects of theinvention. Due to multipath and other phenomena, a transmitted signalmay reach the base station via multiple signal paths. For improvedperformance, rake receiver 256 a is designed with the capability toprocess multiple (and typically strongest) instances of the receivedsignal (or multipaths). Rake receiver 256 a includes a number of fingerprocessors 510, with each finger processor 510 comprising a finger ofthe rake receiver and can be assigned to process a particular multipath.

[0098] As shown in FIG. 5, the complex samples, I_(IN) and Q_(IN), fromreceiver 254 are provided to a number of finger processors 510 a through510 l. Within each assigned finger processor 510, the I_(IN) and Q_(IN)samples are provided to a PN despreader 520, which also receives acomplex PN sequence, PNI and PNQ. The complex PN sequence is generatedin accordance with the particular design of the CDMA system beingimplemented and, for some CDMA systems, is generated by multiplying theshort IPN and QPN sequences with the long PN sequence by multipliers 538a and 538 b. The short IPN and QPN sequences are used to spread the dataat the transmitting remote terminal, and the long PN sequence isassigned to the remote terminal and may be used to scramble the data.The PNI and PNQ sequences are generated with a time offset correspondingto that of the multipath being processed by that finger processor.

[0099] PN despreader 520 performs a complex multiply of the complexI_(IN) and Q_(IN) samples with the complex PN sequence and providescomplex despread I_(DES) and Q_(DES) samples to decover elements 522 and532. Decover element 522 decovers the despread samples with one or morechannelization codes (e.g., Walsh codes) that were used to cover thedata and generates complex decovered samples. The decovered samples arethen provided to a symbol accumulator 524 that accumulates the samplesover the length of the channelization code to generate decoveredsymbols. The decovered symbols are then provided to a pilot demodulator526.

[0100] For some CDMA systems, a pilot reference is transmitted during aportion of the uplink transmission (e.g., as shown in FIG. 3). Thus,decover element 532 decovers the despread samples with the particularchannelization code (e.g., a Walsh code 0 for some CDMA systems, or anOVSF code of 0 for a W-CDMA system) that was used to cover the pilot atthe remote terminal. The decovered pilot samples are then provided to anaccumulator 534 and accumulated over a particular time interval togenerate samples y_(i), for i=1, . . . , N_(P), corresponding to pilotsymbols. The accumulation time interval can be the duration of the pilotchannelization code, an entire pilot reference period, or some othertime interval. The samples y_(i) corresponding to pilot symbols are thenprovided to a pilot filter 410.

[0101] Similarly, during non-pilot symbol periods, decover element 532decovers the despread samples with the particular channelization codeused to cover the non-pilot symbols at the remote terminal. Thedecovered non-pilot samples may be accumulated over a particular timeinterval by accumulator 534 to generate samples y_(i), for i=N_(P)1+, .. . , N_(T), corresponding to non-pilot symbols. The accumulation timeinterval used for samples corresponding to non-pilot symbols may be thesame or different from that used for samples corresponding to pilotsymbols. The samples y_(i) corresponding to non-pilot symbols are alsoprovided to pilot filter 410.

[0102] Pilot filter 410 may be implemented with any one of the pilotfilter designs described above in FIGS. 4A through 4C or some otherdesign. Pilot filter 410 generates pilot estimates based on the samplesy_(i) corresponding to pilot and non-pilot symbols and provides thepilot estimates to pilot demodulator 526. Although not shown in FIG. 5,pilot filter 410 may further receive and utilizes the samples for otherdata symbols (e.g., from symbol accumulator 524) to generate the pilotestimates. Pilot filter 410 typically provides a pilot estimate for eachdata sample to be demodulated. Depending on the specific implementation,pilot filter 410 may perform interpolation on the FIR or IIR filteroutput ƒ_(k) to generate the required pilot estimates.

[0103] Pilot demodulator 526 performs coherent demodulation of thedecovered symbols from symbol accumulator 524 with the pilot estimatesfrom pilot filter 536 and provides demodulated symbols to a symbolcombiner 540. Coherent demodulation can be achieved by performing a dotproduct and a cross product of the decovered symbols with the pilotestimates. The dot and cross products effectively perform a phasedemodulation of the data and further scale the resultant output by therelative strength of the recovered pilot. The scaling with the pilotseffectively weighs the contributions from different multipaths inaccordance with the quality of the multipaths for efficient combining.The dot and cross products thus perform the dual role of phaseprojection and signal weighting that are characteristics of a coherentrake receiver.

[0104] Symbol combiner 540 receives and coherently combines thedemodulated symbols from all assigned finger processors 510 to providerecovered symbols for a particular received signal being processed bythe rake receiver. The recovered symbols for all received signals maythen be combined to generate overall recovered symbols that are thenprovided to the subsequent processing element.

[0105] Searcher element 512 can be designed to search for strongmultipaths of the received signal at numerous time offsets, and themultipaths having the highest signal quality measurements are selected.The available finger processors 510 are then assigned to process thesemultipaths.

[0106] For simplicity, various aspects and embodiments of the pilotfilter have been described for a specific implementation in a basestation of a CDMA system. The pilot filter may also be implemented andused in the remote terminal of the CDMA system. In general, the pilotfilter described herein may be advantageously used in any wirelesscommunication system in which a pilot is transmitted in a non-continuousmanner and other information is available for use.

[0107] The pilot filter may be implemented in hardware, software,firmware, or a combination thereof. For a hardware design, the pilotfilter may be implemented within a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a processor, amicroprocessor, a controller, a microcontroller, a field programmablegate array (FPGA), a programmable logic device, other electronic unit,or any combination thereof. And for a software or firmware design, thepilot filter may be implemented with codes executed by a processor(e.g., controller 230 or 270 in FIG. 2).

[0108] The previous description of the disclosed embodiments is providedto enable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thespirit or scope of the invention. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

1. A method of improving the accuracy of a channel estimate by a pilotfilter, comprising: generating samples corresponding to pilot symbolsand non-pilot symbols; assigning a non-fixed weight to each of one ormore non-pilot symbols, the non-fixed weight being variable and afunction of the samples corresponding to the associated non-pilotsymbol; and using the assigned non-fixed weights for the one or morenon-pilot symbols to generate the channel estimate.
 2. The method ofclaim 1, wherein the pilot filter is a CDMA filter.
 3. The method ofclaim 2, wherein the CDMA filter is a W-CDMA filter.
 4. A method forgenerating pilot estimates indicative of characteristics of acommunication link, comprising: receiving samples corresponding to pilotsymbols and non-pilot symbols; weighting samples corresponding to pilotsymbols in accordance with a first set of one or more coefficients toprovide first weighted samples; weighting samples corresponding tonon-pilot symbols in accordance with a second set of one or morecoefficients to provide second weighted samples; and generating thepilot estimates based on the first and second weighted samples.
 5. Themethod of claim 4, further comprising: updating the one or morecoefficients in the second set based on the samples corresponding tonon-pilot symbols.
 6. The method of claim 5, wherein the one or morecoefficients in the second set are updated further based on the pilotestimates.
 7. The method of claim 6, wherein the one or morecoefficients in the second set are updated further based on a valueindicative of the quality of the samples used to update thecoefficients.
 8. The method of claim 6, wherein the one or morecoefficients in the second set are updated further based on a valueindicative of a signal-to-noise-plus-interference ratio (SNR) of thesamples used to update the coefficients.
 9. The method of claim 7,wherein the coefficients in the second set are updated to larger valuesif the quality of the samples is high, and to lower values if thequality of the samples is low.
 10. The method of claim 4, wherein theone or more coefficients in the second set are updated as:${\tan \quad {h\left( {\frac{1}{\sigma^{2}}{Re}\left\{ {f_{k - 1}y_{i}^{*}} \right\}} \right)}},$

where ƒ_(k−1) is the pilot estimate for a prior time instance k−1, y_(i)are samples corresponding to non-pilot symbols, and 1/σ² isrepresentative of the quality of the samples used to update thecoefficients.
 11. The method of claim 10, wherein the tanh function isapproximated with a piece-wise linear function.
 12. The method of claim10, wherein the term 1/σ² is approximated with a constant.
 13. Themethod of claim 4, wherein the coefficients in the first and second setare quantized to L bits, where L is 5 or less.
 14. The method of claim4, wherein the coefficients in the second set have magnitude equal to orless than the magnitude of the coefficients in the first set.
 15. Themethod of claim 4, wherein the coefficients in the first set have equalmagnitude.
 16. The method of claim 4, wherein the pilot and non-pilotsymbols are time-division multiplexed in a CDMA data transmission. 17.The method of claim 16, wherein the CDMA data transmission conforms toW-CDMA standard.
 18. A pilot filter in a wireless communication system,comprising: one or more multipliers configured to receive and weighsamples corresponding to pilot symbols with one or more firstcoefficients to provide first weighted samples, and to receive and weighsamples corresponding to non-pilot symbols with one or more secondcoefficients to provide second weighted samples; and a summer coupled tothe one or more multipliers and configured to receive and combined thefirst and second weighted samples to provide pilot estimates.
 19. Thepilot filter of claim 18, further comprising: a coefficient adjustmentunit configured to receive the samples corresponding to the non-pilotsymbols and the pilot estimates, and to update the one or more secondcoefficients based on the received samples and pilot estimates.
 20. Thepilot filter of claim 19, wherein the coefficient adjustment unit isfurther configured to update the one or more second coefficients basedon the quality of the samples used to update the coefficients.
 21. Thepilot filter of claim 18, and implemented with a finite impulse response(FIR) filter structure.
 22. The pilot filter of claim 18, andimplemented with an infinite impulse response (IIR) filter structure.23. The pilot filter of claim 18, wherein the first and secondcoefficients are quantized to L bits, where L is 5 or less.
 24. Thepilot filter of claim 18, wherein the samples corresponding to pilot andnon-pilot symbols are derived from a CDMA data transmission.
 25. A rakereceiver in a wireless communication system, comprising: a plurality offinger processors, each finger processor configurable to process arespective instance of a received signal, each finger processor furtherincluding a despreader configured to receive and despread digitizedsamples in accordance with one or more pseudo-noise (PN) sequences toprovide despread samples, a first processor coupled to the despreaderand configured to receive and process the despread samples to providefirst samples, a second processor coupled to the despreader andconfigured to receive and process the despread samples to provide secondsamples, a pilot filter coupled to the second processor and configuredto receive and filter the second samples to provide pilot estimates,wherein the pilot filter is further configured to weigh samplescorresponding to pilot symbols with a first set of one or more weightsand to weigh samples corresponding to non-pilot symbols with a secondset of one or more weights, and a pilot demodulator coupled to the firstprocessor and the pilot filter and configured to receive and demodulatethe first samples with the pilot estimates to provide recovered symbols.